Triple
T742760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Mule |
E15277
|
entity |
| Predicate | numberOfIndividuals |
P5741
|
FINISHED |
| Object | multiple mules over time |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: multiple mules over time | Statement: [Army Mule, numberOfIndividuals, multiple mules over time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIndividuals Context triple: [Army Mule, numberOfIndividuals, multiple mules over time]
-
A.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
B.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
C.
numberOfIndicators
Indicates the total count of indicators associated with or relevant to a given entity or context.
-
D.
numberOfConstituents
chosen
Indicates the total count of individual components or members that make up a larger whole or group.
-
E.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a60f92d08190a4f44c5b4d068ab5 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fdaaf48190985f62acfc069508 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.